Abstract for presentation at Spatial Sciences Institute International Biennial Conference

A framework of environmental modelling and information sharing for urban air pollution control and management

  • Gang-Jun Liu, RMIT University, Australia
  • Erjiang Fu, Melbourne University, Australia
  • Yunjia Wang, China University of Mining and Technology, RMIT University Senior Visiti, China
  • Kefei Zhang, RMIT University, Australia
  • Colin Arrowsmith, RMIT University, Australia
  • Baoping Han, China University of Mining Technology, China

    • In most metropolitan areas in countries like China and India, urban air pollution has become a serious environmental issue that poses adverse impacts on human and environmental health. Urban air pollution in Asia is expected to increase considerably over the next three decades due to rising levels of economic growth and energy consumption. Effective control of urban air pollution poses a challenge to both researchers and administrators around the world, due to the heterogeneous and dynamic nature of urban environments.
    Environmental monitoring and spatial modeling, with spatial and temporal resolutions suitable for the sampling and simulation of urban air pollution, enable a better characterization of the dynamic spatial patterns of (1) the source, substance and dispersion rates of urban air pollution, and (2) the levels of concentration of air pollution at every location over a particular urban area. Such a characterization establishes an objective foundation for formulating a better understanding of the interrelationships among urban air pollution emissions, meteorological conditions, 3D urban settings, pollution dispersion processes, ambient air pollution concentration, environmental exposure and the impact of urban air pollution on human and the environment. This understanding, in turn, is a prerequisite for finding effective solutions to problems associated with urban air pollution, such as feasible health and environment based standards and cost-effective pollution control measures.
    In this paper, we demonstrate that spatial information technologies, such as remote sensing, global positioning systems, geographic information systems and geovisualization can facilitate effective and efficient capture, management, analysis and visualization of voluminous environmental observations. They enable environmental monitoring and spatial modelling with spatial and temporal resolutions appropriate for better spatial-temporal characterisation of urban air pollution.
    Key word: urban air pollution, environmental monitoring, spatial modelling, spatial information technologies

    Conference Organiser - ICMS Pty Ltd